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AxLabs

Banana Accounting MCP Server

by AxLabs

Account budget

banana_budget
Read-only

Retrieve budget figures for an account, group, or balance class, with support for periods, frequencies, and filters.

Instructions

Return the budget figure for an account, group or balance class. Supports period, frequency and filter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
docNoAccounting document name as opened in Banana (e.g. "accounting.ac2"). Append "_p1", "_p2" for previous years. Defaults to BANANA_DEFAULT_DOC if set.
typeYesAmount type to return (opening, credit, debit, total, balance, *currency, rowcount).
filterNoJavaScript expression to filter transactions, e.g. filter=row.value("Date")==="2024-01-15". Available: row, rowNr, table.
periodNoPeriod filter: an abbreviation like "Q1"/"3M"/"1Y" or a date range "2024-01-01/2024-03-31".
accountYesAccount/group/class selector: an account id ("1000"), group ("Gr=6"), balance class ("BClass=1"), or pipe-separated accounts ("1000|1010|1020").
frequencyNoFrequency: D=daily, W=weekly, M=monthly, Q=quarterly, S=semesterly, Y=yearly.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations declare readOnlyHint=true and openWorldHint=true, which already establish the safety profile. The description adds useful behavioral context by noting support for period, frequency, and filtering, and by specifying that it returns a budget figure for account/group/class selectors. While it doesn't describe the exact return format, the term 'figure' suggests a scalar value, and annotations cover the rest.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that efficiently conveys the core purpose and key capabilities without any filler. Every word contributes to understanding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (6 params, 2 required, no output schema), the description plus schema covers the necessary information. The description indicates it returns a budget figure, and the schema explains the parameters. It could be slightly more explicit about what a 'budget figure' means, but overall it's complete for this level of complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description does not add meaning beyond the schema; it merely mentions 'period, frequency and filter' without additional detail. The schema's parameter descriptions already fully document each field.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns a budget figure for an account, group, or balance class, with a specific verb and resource. It distinguishes itself from related sibling tools like banana_budget_card and banana_budget_interest by focusing on the raw budget figure.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on what the tool supports (period, frequency, filter), implying when to use it for budget lookups. It doesn't explicitly name alternatives or exclusions, but the context is sufficient for an agent to infer typical usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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